# Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement)

> **NIH NIH UL1** · MAYO CLINIC ROCHESTER · 2020 · $153,686

## Abstract

Project Summary: The Clinical and Translational Science Award (CTSA) program funded by the National
Center for Advancing Translational Sciences (NCATS) seeks to improve the efficiency, quality and impact of
the process for turning observations in the laboratory, clinic and community into interventions that improve the
health of individuals and the public. The Mayo Clinic Center for Clinical and Translational Science (CCaTS)
aims to support the translational biomedical discoveries that will drive innovation to improved health.
Management of a CTSA award often requires formal Prior Approval from NCATS including requests for
changes in key personnel, the addition of a foreign component, and to carryover funds as well as requests for
Prior Approval for Delayed Onset Human Subjects Research and Vertebrate Animal Research for nearly all
new KL2 Scholar projects and Pilot Awards. Efficient, clear and well-developed submissions result in
substantially faster approvals. This proposal seeks to leverage the Mayo Clinic CCaTS administrative expertise
to implement a Continuous Quality Improvement (CQI) process to improve outcomes and impact the speed
with which interventions result in improved health.

## Key facts

- **NIH application ID:** 10151843
- **Project number:** 3UL1TR002377-04S3
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Claudia F. Lucchinetti
- **Activity code:** UL1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $153,686
- **Award type:** 3
- **Project period:** 2017-09-18 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10151843

## Citation

> US National Institutes of Health, RePORTER application 10151843, Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement) (3UL1TR002377-04S3). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10151843. Licensed CC0.

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